Development of the CO2 Adsorption Model on Porous Adsorbent Materials Using Machine Learning Algorithms

• Published in: ACS applied energy materials Vol. 7; no. 19; pp. 8596 - 8609
• Main Authors: Mashhadimoslem, Hossein, Abdol, Mohammad Ali, Zanganeh, Kourosh, Shafeen, Ahmed, AlHammadi, Ali A., Kamkar, Milad, Elkamel, Ali
• Format: Journal Article
• Language: English
• Published: American Chemical Society 14-10-2024
• Subjects: carbon-based adsorbent; porous polymers; zeolites; MOFs; machine learning; CO2 adsorption
• ISSN: 2574-0962; 2574-0962
• DOI: 10.1021/acsaem.4c01465

Porous adsorbents have common characteristics, such as high porosity and a large specific surface area. These characteristics, attributed to the internal structure of the material, significantly affect their adsorption performance. In this research study, we created a data set and collected data points from porous adsorbents (2789) from 21 published papers, including carbon-based, porous polymers, metal–organic frameworks (MOFs), and zeolites, to understand their characteristics for CO2 adsorption. Different machine learning (ML) algorithms, such as NN, MLP-GWO, XGBoost, RF, DT, and SVM, have been applied to display the CO2 adsorption performance as a function of characteristics and adsorption isotherm parameters. XGBoost was selected as the best ML algorithm due to its highest accuracy (R 2 = 0.9980; MSE = 0.0001). The predicted results revealed that the adsorption pressure parameter is the most effective in all of the mentioned porous adsorbents. With regard to materials type, while carbon-based materials require higher pressures for a more effective CO2 adsorption, MOFs exhibit a higher potential for adsorbing CO2 under lower pressure conditions. The study also revealed that carbon-based adsorbents, zeolites, and porous polymers with smaller pore diameters demonstrate a high level of CO2 uptake. In contrast, the adsorption performance of MOFs does not show a consistent trend with respect to pore sizes. Also, in all adsorbents, the effect of a pore size smaller than 1 nm on more CO2 adsorption was evident.